Rajkumar Verma
Impact in
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- Multi-Criteria Decision Making
- Fuzzy and Soft Set Theory
- Statistics and Probability top 1%
- Fuzzy Systems and Optimization
Papers in
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- Multi-Criteria Decision Making 43
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- Fuzzy Systems and Optimization 23
- Advanced Statistical Methods and Models 3
- Co-authors
- Bhu Dev Sharma (8 shared papers)José M. Merigó (11 shared papers)Eduardo Álvarez‐Miranda (2 shared papers)Amit Mittal (1 shared paper)Abha Aggarwal (4 shared papers)Christian A. Cancino (1 shared paper)Johann Sienz (1 shared paper)J. Richard Kyle (1 shared paper)
In The Last Decade
Rajkumar Verma
50 papers receiving 803 citations
Peers
Comparison fields: 5 of 85
- Management Science and Operations Research 720
- Statistics and Probability 283
- Computational Theory and Mathematics 202
- Control and Systems Engineering 277
- Artificial Intelligence 214
Countries citing papers authored by Rajkumar Verma
This map shows the geographic impact of Rajkumar Verma's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Rajkumar Verma with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rajkumar Verma more than expected).
Fields of papers citing papers by Rajkumar Verma
This network shows the impact of papers produced by Rajkumar Verma. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Rajkumar Verma. The network helps show where Rajkumar Verma may publish in the future.
Co-authors
The 20 scholars most cited alongside Rajkumar Verma, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 53 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 64 | |
| 2 | 2020 | 60 | |
| 3 | 2020 | 46 | |
| 4 | 2022 | 45 | |
| 5 | Exponential entropy on intuitionistic fuzzy sets | 2013 | 43 |
| 6 | 2015 | 39 | |
| 7 | 2014 | 38 | |
| 8 | 2011 | 30 | |
| 9 | 2020 | 28 | |
| 10 | 2022 | 27 | |
| 11 | 2013 | 23 | |
| 12 | 2020 | 20 | |
| 13 | 2020 | 20 | |
| 14 | 2016 | 20 | |
| 15 | 2021 | 19 | |
| 16 | 2014 | 18 | |
| 17 | 2021 | 18 | |
| 18 | 2015 | 17 | |
| 19 | 2024 | 17 | |
| 20 | Intuitionistic Fuzzy Jensen-Rényi Divergence: Applications to Multiple-Attribute Decision Making | 2013 | 16 |
About Rajkumar Verma
Rajkumar Verma is a scholar working on Management Science and Operations Research, Statistics and Probability, Control and Systems Engineering, Artificial Intelligence and Computational Theory and Mathematics, having authored 53 papers that have together received 838 indexed citations. Recurring topics across this work include Multi-Criteria Decision Making (43 papers), Fuzzy Systems and Optimization (23 papers), Optimization and Mathematical Programming (19 papers), Fuzzy Logic and Control Systems (11 papers), Rough Sets and Fuzzy Logic (9 papers), Advanced Statistical Methods and Models (3 papers), Intuitionistic Fuzzy Systems Applications (3 papers) and Evaluation Methods in Various Fields (3 papers). The work is most often cited by research in Management Science and Operations Research (720 citations), Statistics and Probability (283 citations), Computational Theory and Mathematics (202 citations), Control and Systems Engineering (277 citations) and Artificial Intelligence (214 citations). Rajkumar Verma has collaborated with scholars based in India, Chile and Australia. Frequent co-authors include Bhu Dev Sharma, José M. Merigó, Eduardo Álvarez‐Miranda, Amit Mittal, Abha Aggarwal, Christian A. Cancino, Johann Sienz, J. Richard Kyle, Anna M. Gil‐Lafuente and Brent A. Elliott. Their work appears in journals such as Journal of Intelligent & Fuzzy Systems, International Journal of Intelligent Systems, Soft Computing, Granular Computing and International Journal of Machine Learning and Cybernetics.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.